Devavrat Shah

Causal Inference for Sequential Settings under Interference and Latent Confounding

Phevos Paschalidis, Constantinos Daskalakis, Devavrat Shah

We study causal inference under outcome interference for sequential, observational settings. Specifically, we consider settings where the binary outcomes over N units are Markovian across T time steps. At each time step, the outcomes of N units have dependencies captured through…Read more